The University of Sydney and CSIRO are pleased to host the 5th International Workshop on Guided Self-Organization, September 26-28, 2012 (Sydney, Australia).

Research Aims and Topics

The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization while still being able to direct the outcome of the self-organizing process. GSO typically has the following features: (i) an increase in organization (structure and/or functionality) over some time; (ii) the local interactions are not explicitly guided by any external agent; (iii) task-independent objectives are combined with task-dependent constraints.

What is common to many examples of GSO is the characterization of a system-environment loop (e.g., sensorimotor or perception-action loop) in information-theoretic terms. For instance, given an agent's behavior, the empowerment measures the amount of Shannon information that the agent can "inject into" its sensors through the environment, affecting future actions and future perceptions. On the other hand, maximization of the predictive information or excess entropy enables an adaptive/evolutionary change in controllers' logic in such a way that the system becomes coordinated. Methods relying on the use of predictive information in a sensorimotor process may produce explicit learning rules for the agent optimizing its behavior. However, the lack of a broadly applicable mathematical framework across multiple scales and contexts leaves GSO methodology incomplete. Devising such a framework and identifying common principles of guidance are the main themes of GSO workshops.

The GSO-2012 workshop will bring together invited experts and researchers in self-organizing systems, with particular emphasis on the information- and graph-theoretic foundations of GSO and the information dynamics of adaptive systems. The following topics are of special interest: information-theoretic measures of complexity, nonlinear dynamics, complex networks, information-driven self-organization (IDSO), applications of GSO to systems biology, computational neuroscience, cooperative and modular robotics, swarm intelligence, and machine learning.

The program includes 3 days, each day with two keynote talks, and five-six regular presentations.